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On the Measurement of Hedging Effectiveness for Long-Term Investment Guarantees

Author

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  • Maciej Augustyniak

    (Département de Mathématiques et de Statistique, Université de Montréal, P.O. Box 6128, Station Centre-Ville, Montreal, QC H3C 3J7, Canada
    Quantact Actuarial and Financial Mathematics Laboratory, Centre de Recherches Mathématiques, Université de Montréal, P.O. Box 6128, Station Centre-Ville, Montreal, QC H3C 3J7, Canada)

  • Alexandru Badescu

    (Department of Mathematics and Statistics, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada)

  • Mathieu Boudreault

    (Quantact Actuarial and Financial Mathematics Laboratory, Centre de Recherches Mathématiques, Université de Montréal, P.O. Box 6128, Station Centre-Ville, Montreal, QC H3C 3J7, Canada
    Département de Mathématiques, Université du Québec à Montréal, P.O. Box 8888, Station Centre-Ville, Montreal, QC H3C 3P8, Canada)

Abstract

Although the finance literature has devoted a lot of research into the development of advanced models for improving the pricing and hedging performance, there has been much less emphasis on approaches to measure dynamic hedging effectiveness. This article discusses a statistical framework based on regression analysis to measure the effectiveness of dynamic hedges for long-term investment guarantees. The importance of taking model risk into account is emphasized. The difficulties in reducing hedging risk to an appropriately low level lead us to propose a new perspective on hedging, and recognize it as a tool to modify the risk–reward relationship of the unhedged position.

Suggested Citation

  • Maciej Augustyniak & Alexandru Badescu & Mathieu Boudreault, 2023. "On the Measurement of Hedging Effectiveness for Long-Term Investment Guarantees," JRFM, MDPI, vol. 16(2), pages 1-18, February.
  • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:2:p:112-:d:1065025
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    References listed on IDEAS

    as
    1. Bakshi, Gurdip & Cao, Charles & Chen, Zhiwu, 1997. "Empirical Performance of Alternative Option Pricing Models," Journal of Finance, American Finance Association, vol. 52(5), pages 2003-2049, December.
    2. Nathan Lassance & Frédéric Vrins, 2018. "A comparison of pricing and hedging performances of equity derivatives models," Applied Economics, Taylor & Francis Journals, vol. 50(10), pages 1122-1137, February.
    3. Andreas Kaeck, 2013. "Hedging Surprises, Jumps, and Model Misspecification: A Risk Management Perspective on Hedging S&P 500 Options," Review of Finance, European Finance Association, vol. 17(4), pages 1535-1569.
    4. Trottier, Denis-Alexandre & Godin, Frédéric & Hamel, Emmanuel, 2018. "Local Hedging Of Variable Annuities In The Presence Of Basis Risk," ASTIN Bulletin, Cambridge University Press, vol. 48(2), pages 611-646, May.
    5. Bjørn Eraker & Michael Johannes & Nicholas Polson, 2003. "The Impact of Jumps in Volatility and Returns," Journal of Finance, American Finance Association, vol. 58(3), pages 1269-1300, June.
    6. Eraker, Bjorn & Johannes, Michael & Polson, Nicholas, 2002. "The Impact of Jumps in Volatility and Returns," Working Papers 02-18, Duke University, Department of Economics.
    7. Bernard Dumas & Jeff Fleming & Robert E. Whaley, 1998. "Implied Volatility Functions: Empirical Tests," Journal of Finance, American Finance Association, vol. 53(6), pages 2059-2106, December.
    8. Hull, John & White, Alan, 2017. "Optimal delta hedging for options," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 180-190.
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